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Record W2419541696

Pathological burst fracture in the cervical spine with negative red flags: a case report.

2016· article· en· W2419541696 on OpenAlexaff
Jocelyn Cox, Chris deGraauw, Erik Klein

Bibliographic record

VenuePubMed · 2016
Typearticle
Languageen
FieldMedicine
TopicSpinal Fractures and Fixation Techniques
Canadian institutionsCanadian Memorial Chiropractic College
Fundersnot available
KeywordsPathologicalBurst fractureCervical spineMedicineLesionCervical vertebraePathologyPhysical therapyAnatomySurgery
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To report on a case of a pathological burst fracture in the cervical spine where typical core red flag tests failed to identify a significant lesion, and to remind chiropractors to be vigilant in the recognition of subtle signs and symptoms of disease processes. CLINICAL FEATURES: A 61-year-old man presented to a chiropractic clinic with neck pain that began earlier that morning. After a physical exam that was relatively unremarkable, imaging identified a burst fracture in the cervical spine. INTERVENTION & OUTCOMES: The patient was sent by ambulance to the hospital where he was diagnosed with multiple myeloma. No medical intervention was performed on the fracture. SUMMARY: The patient's initial physical examination was largely unremarkable, with an absence of clinical red flags. The screening tools were non-diagnostic. Pain with traction and the sudden onset of symptoms prompted further investigation with plain film imaging of the cervical spine. This identified a pathological burst fracture in the C4 vertebrae.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.006
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.003
Science and technology studies0.0050.003
Scholarly communication0.0030.002
Open science0.0030.003
Research integrity0.0110.004
Insufficient payload (model declined to judge)0.0030.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.269
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2016
Admission routes1
Has abstractyes

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